ab10c6b4c0
Model: jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun Source: Original Platform
82 lines
3.3 KiB
Markdown
82 lines
3.3 KiB
Markdown
---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-hh-helpful-4xh200
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tags:
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- alignment-handbook
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- new-dpo
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- generated_from_trainer
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datasets:
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- Anthropic/hh-rlhf
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model-index:
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- name: llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-helpful-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-helpful-4xh200) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6074
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- Fcm Dpo/beta: 0.0011
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- Fcm Dpo/q T: 0.4332
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- Fcm Dpo/delta: 0.0239
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- Fcm Dpo/margin: 270.7279
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- Margin Dpo/margin Mean: 270.7279
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- Margin Dpo/margin Std: 601.7490
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- Logps/chosen: -823.2324
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- Logps/rejected: -1101.7070
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- Logps/ref Chosen: -79.0510
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- Logps/ref Rejected: -86.7979
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- Logits/chosen: -1.0197
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- Logits/rejected: -1.0177
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 64
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- total_eval_batch_size: 32
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------:|:-------------:|:--------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
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| 1.0801 | 0.2937 | 200 | 0.6239 | 0.0049 | 0.4392 | 0.0321 | 58.0086 | 58.0086 | 147.6546 | -225.8390 | -291.5945 | -79.0510 | -86.7979 | -0.3472 | -0.3330 |
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| 1.0433 | 0.5874 | 400 | 0.6033 | 0.0019 | 0.4336 | 0.0376 | 156.9007 | 156.9006 | 328.4540 | -532.2333 | -696.8809 | -79.0510 | -86.7979 | -0.5230 | -0.5119 |
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| 1.1393 | 0.8811 | 600 | 0.6074 | 0.0011 | 0.4332 | 0.0239 | 270.7279 | 270.7279 | 601.7490 | -823.2324 | -1101.7070 | -79.0510 | -86.7979 | -1.0197 | -1.0177 |
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### Framework versions
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- Transformers 4.51.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.21.4
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